Learning Theory

A Generalized Neural Tangent Kernel Analysis for Two-layer Neural Networks NeurIPS 2020 Agnostic Q-learning with Function Approximation in Deterministic Systems: Near-Optimal Bounds on Approximation Error and Sample Complexity NeurIPS 2020 Agnostic Learning of a Single Neuron with Gradient Descent NeurIPS 2020 Algebraic and Analytic Approaches for Parameter Learning in Mixture Models ALT 2020 Algorithms and SQ Lower Bounds for PAC Learning One-Hidden-Layer ReLU Networks COLT 2020 A Limitation of the PAC-Bayes Framework NeurIPS 2020 Almost Optimal Model-Free Reinforcement Learningvia Reference-Advantage Decomposition NeurIPS 2020 A Matrix Chernoff Bound for Markov Chains and Its Application to Co-occurrence Matrices NeurIPS 2020 A Mean Field Analysis Of Deep ResNet And Beyond: Towards Provably Optimization Via Overparameterization From Depth ICML 2020 An analytic theory of shallow networks dynamics for hinge loss classification NeurIPS 2020 A Nearly Optimal Variant of the Perceptron Algorithm for the Uniform Distribution on the Unit Sphere COLT 2020 An empirical analysis of existing systems and datasets toward general simple question answering COLING 2020 A new regret analysis for Adam-type algorithms ICML 2020 A Non-Trivial Algorithm Enumerating Relevant Features over Finite Fields ALT 2020 An Optimal Elimination Algorithm for Learning a Best Arm NeurIPS 2020 Approximate Cross-Validation in High Dimensions with Guarantees AISTATS 2020 Approximate is Good Enough: Probabilistic Variants of Dimensional and Margin Complexity COLT 2020 Approximation Schemes for ReLU Regression COLT 2020 A random matrix analysis of random Fourier features: beyond the Gaussian kernel, a precise phase transition, and the corresponding double descent NeurIPS 2020 A Re-evaluation of Knowledge Graph Completion Methods ACL 2020 Are Transformers universal approximators of sequence-to-sequence functions? ICLR 2020 A Sample Complexity Separation between Non-Convex and Convex Meta-Learning ICML 2020 A Score-and-Search Approach to Learning Bayesian Networks with Noisy-OR Relations PGM 2020 Assessing Local Generalization Capability in Deep Models AISTATS 2020 A Statistical Learning Approach to Modal Regression JMLR 2020